A method and system for identifying gold-plated and k-gold samples

Abstract

The application provides a kind of gold plating and K gold sample identification method and system, through X-ray detector, the energy spectrum of the sample to be measured is collected, the original X-ray spectrum of the sample to be measured is obtained, the original X-ray spectrum is smoothed, the target X-ray spectrum of the sample to be measured is obtained, the initial simulation spectrum of the sample to be measured is generated according to the target X-ray spectrum, the initial simulation spectrum is corrected by iterative algorithm, until the deviation of the characteristic peak intensity of each element in the target simulation spectrum obtained after correction and the corresponding element in the target X-ray spectrum meets the preset convergence condition, whether the sample to be measured is gold-plated sample is judged according to the target simulation spectrum, in the above manner, it is favorable to improve the accuracy of detection result, reduce the misjudgment rate in the scene such as thick plating layer misjudgment, similar component confusion.

Description

Technical Field

[0001] This invention relates to the field of precious metal identification technology, and in particular to a method and system for identifying gold-plated and karat gold samples. Background Technology

[0002] X-ray fluorescence (XRF) spectroscopy, with its core advantages of non-destructive testing and rapid analysis, has been widely used in fields such as precious metal composition detection, authenticity identification, and quality grading. It has become one of the mainstream detection technologies in the industry, especially in distinguishing between gold-plated and karat gold samples. However, most XRF testing instruments on the market currently use empirical comparison algorithms to identify gold-plated and karat gold. These algorithms often achieve identification through "standard spectral library memory comparison": first, a large number of standard samples, such as gold-plated and karat gold with different ratios, are pre-collected to construct a standard energy spectrum database; when testing a sample, the system compares the collected energy spectrum of the sample with the standard energy spectra in the database one by one, calculates the similarity, selects the most matching standard curve, and then determines the composition and type of the sample.

[0003] However, the energy spectrum characteristics of gold-plated and karat gold alloy samples have many overlapping areas. Relying solely on the fuzzy matching logic of "optimal similarity" makes it difficult to accurately distinguish between gold-plated and highly similar karat gold samples, which can easily lead to qualitative deviations. Furthermore, for gold-plated samples with thicker coatings, the gold layer can obscure the substrate signal, causing traditional empirical algorithms to often misclassify them as high-purity karat gold or pure gold, resulting in serious deviations in the detection results. Summary of the Invention

[0004] This invention provides a method and system for identifying gold-plated and karat gold samples, which helps to improve the accuracy of detection results.

[0005] To achieve the above objectives, the present invention provides a method for identifying gold-plated and karat gold samples, comprising the following steps: Energy dispersive spectroscopy (EDS) is performed on the sample to obtain the original X-ray spectrum of the sample. The original X-ray spectrum is smoothed to obtain the target X-ray spectrum of the sample to be tested; An initial simulated spectrum of the sample to be tested is generated based on the target X-ray spectrum; The initial simulated spectrum is corrected by a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition. Based on the target simulated spectrum, the sample to be tested is determined to be a gold-plated sample or a karat gold sample.

[0006] Optionally, generating the initial simulated spectrum of the sample to be tested based on the target X-ray spectrum includes: Obtain the peak position of each characteristic peak in the target X-ray spectrum, and determine the peak area and corresponding element of each characteristic peak based on the peak position; Calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area; The initial percentage content of each element is calculated based on the measured characteristic peak intensity of each element; The initial simulated spectrum of the sample to be tested is generated based on the initial percentage content of each element.

[0007] Optionally, the step of calculating the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area includes: The net peak area of ​​each characteristic peak is obtained by subtracting the continuous background area from the peak area of ​​each characteristic peak. The net peak area of ​​each characteristic peak is used as the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum.

[0008] Optionally, the step of calculating the initial percentage content of each element based on the measured characteristic peak intensity of each element includes: Through formula Calculate elements The initial percentage content, of which Represents element The initial percentage content, Represents element The actual characteristic peak intensity, This represents the sum of the measured characteristic peak intensities of all elements, where n is the number of elements.

[0009] Optionally, the step of correcting the initial simulated spectrum using a cyclic iterative algorithm until the characteristic peak intensity deviations of each element in the corrected target simulated spectrum and the corresponding elements in the target X-ray spectrum satisfy a preset convergence condition includes: Step a: Initialize iteration parameters—Use the initial simulated spectrum as the current simulated spectrum for the first iteration, and use the initial percentage content of each element as the original percentage content for the first iteration. ; Step b: Obtain the elements in the current simulated spectrum Theoretical characteristic peak intensity ; Step c: Calculate the elements Theoretical characteristic peak intensity and elements in the target X-ray spectrum Actual characteristic peak intensity Deviation: ; Step d: According to the formula Update elements Original percentage content The updated percentage content is obtained. , where k is the iteration coefficient; Step e: Based on element Updated percentage content Regenerate a new current simulation spectrum; Step f: Determine the elements in the new current simulated spectrum If the deviation of the characteristic peak intensity from the corresponding element in the target X-ray spectrum meets a preset convergence condition, and if not, the new current simulated spectrum is used as the current simulated spectrum for the next iteration, and the element... Updated percentage content As the original percentage content for the next iteration Return to step b and repeat; if satisfied, terminate the iteration and determine the new current simulated spectrum as the target simulated spectrum.

[0010] Optionally, determining whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum includes: The sample to be tested is determined to be a gold-plated sample if it meets both of the following conditions one and two; otherwise, it is determined to be a karat gold sample: Condition 1: The percentage content of Au element in the sample to be tested after the last iteration is less than 99%; Condition 2: The intensity ratio L1 of the La characteristic peak to the Lb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L2 of the La characteristic peak to the Lb characteristic peak of Au in the target simulated spectrum satisfy L1 / L2>1.1; or, the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the target simulated spectrum satisfy L3 / L4<0.8.

[0011] Optionally, generating the initial simulated spectrum of the sample to be tested based on the initial percentage content of each element includes: Using the initial percentage content of each element as a parameter input, the original theoretical characteristic peak intensity of each element is calculated using the basic parameter method model; The original theoretical characteristic peak intensities of each element are corrected based on the pre-set sample structure model; Based on the original theoretical characteristic peak intensities after correction of all elements, spectral lines are synthesized to obtain the initial simulated spectrum that conforms to the preset sample structure corresponding to the sample structure model.

[0012] Optionally, obtaining the peak positions of each characteristic peak in the target X-ray spectrum and determining the peak area and corresponding element of each characteristic peak based on the peak positions includes: The peak positions of candidate characteristic peaks in the X-ray spectrum of the target are obtained using the second derivative method; From the candidate feature peaks, feature peaks with peak heights greater than or equal to a preset peak height threshold are selected to obtain the true feature peaks; The peak area and corresponding element of each true characteristic peak are determined based on the peak position of the true characteristic peak.

[0013] This invention also provides a system for identifying gold-plated and karat gold samples, comprising: The acquisition module is used to acquire the energy spectrum of the sample to be tested and obtain the original X-ray spectrum of the sample. The processing module is used to smooth the original X-ray spectrum to obtain the target X-ray spectrum of the sample to be tested; The generation module is used to generate an initial simulated spectrum of the sample to be tested based on the target X-ray spectrum; The correction module is used to correct the initial simulated spectrum through a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition. The judgment module is used to determine whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum.

[0014] Optionally, the generation module is specifically used for: Obtain the peak position of each characteristic peak in the target X-ray spectrum, and determine the peak area and corresponding element of each characteristic peak based on the peak position; Calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area; The initial percentage content of each element is calculated based on the measured characteristic peak intensity of each element; The initial simulated spectrum of the sample to be tested is generated based on the initial percentage content of each element.

[0015] Beneficial Effects: The present invention provides a method for identifying gold-plated and karat gold samples. This method involves acquiring the energy spectrum of the sample using an X-ray detector to obtain its original X-ray spectrum. The original X-ray spectrum is then smoothed to obtain the target X-ray spectrum. An initial simulated spectrum of the sample is generated based on the target X-ray spectrum. This initial simulated spectrum is then corrected using an iterative algorithm until the characteristic peak intensity deviation between each element in the corrected target simulated spectrum and the corresponding element in the target X-ray spectrum meets a preset convergence condition. The method determines whether the sample is gold-plated based on the target simulated spectrum. Thus, the present invention optimizes the matching degree between the simulated spectrum and the measured spectrum through iterative optimization until they reach an optimal fit. Based on this optimal matching result, the actual structural characteristics of the sample (such as a coating-substrate composite structure or a homogeneous alloy structure) can be accurately analyzed, thereby achieving accurate differentiation between gold-plated and karat gold samples and reducing the misjudgment rate in scenarios such as thick coating misjudgment and confusion due to similar components. Attached Figure Description

[0016] The technical solution and its beneficial effects of the present invention will become apparent from the following detailed description of specific embodiments in conjunction with the accompanying drawings.

[0017] Figure 1 This is a flowchart illustrating a method for identifying gold-plated and karat gold samples according to the present invention. Figure 2 yes Figure 1 A flowchart illustrating step S103 in the identification method shown; Figure 3 This is a schematic diagram of the structure of an identification system for gold-plated and karat gold samples according to the present invention; Figure 4 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum during the first iteration in the identification method of the present invention; Figure 5 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several iterations in the identification method of the present invention. Figure 6 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several iterations in the identification method of the present invention. Figure 7 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several iterations in the identification method of the present invention. Figure 8 This is a schematic diagram of the output interface of the identification method of the present invention, which identifies the sample as a gold-plated sample; Figure 9 This is a schematic diagram of the output interface of the identification method of the present invention, which identifies the sample as a karat gold sample; Figure 10This is a test data table for verifying multiple groups of gold-plated and karat gold samples in the identification method of the present invention. Detailed Implementation

[0018] Please refer to the diagrams, where the same component symbols represent the same components. The principles of the invention are illustrated by way of example implemented in a suitable computing environment. The following description is based on the illustrative specific embodiments of the invention and should not be construed as limiting the invention to other specific embodiments not detailed herein.

[0019] participate Figure 1 This invention provides a method for identifying gold-plated and karat gold samples, comprising the following steps: Step S101: Perform energy spectrum acquisition on the sample to be tested to obtain the original X-ray spectrum of the sample.

[0020] The sample to be tested can be, for example, jewelry, precious metal ornaments, etc. The energy spectrum of the sample can be acquired using an XRF (X-ray Fluorescence Spectrometer). For instance, the sample is placed on the sample stage of the XRF spectrometer, the instrument is activated to excite the sample with X-rays, and the emitted X-ray energy spectrum signal is acquired to generate a raw X-ray spectrum. The horizontal axis of this raw X-ray spectrum represents the X-ray energy (unit: keV), and the vertical axis represents the signal count rate (unit: cps), directly reflecting the fluorescence signal distribution of each element in the sample.

[0021] Step S102: Smooth the original X-ray spectrum to obtain the target X-ray spectrum of the sample to be tested.

[0022] By smoothing the original X-ray spectrum, random fluctuations such as detector noise and environmental electromagnetic interference can be filtered out, preventing these interference signals from affecting the accuracy of subsequent characteristic peak identification. Moving average or Gaussian smoothing algorithms can be used to smooth the original X-ray spectrum to obtain a target X-ray spectrum with a stable signal baseline and clear characteristic peaks.

[0023] Step S103: Generate the initial simulated spectrum of the sample to be tested based on the target X-ray spectrum.

[0024] Specifically, such as Figure 2 As shown, step S103 includes the following sub-steps: Sub-step S1031: Obtain the peak position of each characteristic peak in the target X-ray spectrum, and determine the peak area and corresponding element of each characteristic peak based on the peak position.

[0025] Specifically, the second derivative method is used to obtain the peak positions of candidate characteristic peaks in the target X-ray spectrum; characteristic peaks with peak heights greater than or equal to a preset peak height threshold are selected from the candidate characteristic peaks to obtain the true characteristic peaks; and the peak area and corresponding elements of each true characteristic peak are determined based on the peak positions of the true characteristic peaks.

[0026] By performing second-order derivative calculations on the target X-ray spectrum, based on the signal characteristics of X-ray fluorescence spectroscopy, the apex of a characteristic peak corresponds to an extreme point of signal intensity. In the second-order derivative curve, the derivative value at this extreme point is 0. Therefore, by traversing the second-order derivative curve, all points where the derivative is 0 are located, and these points are used as the peak positions of candidate characteristic peaks. The candidate characteristic peak positions not only include the true characteristic peaks of the analyte but may also contain noise spurious peaks formed by detector noise and environmental interference. The signal intensity of such spurious peaks is usually much lower than that of the true characteristic peaks. Therefore, based on the characteristic peak signal characteristics of the target element (e.g., precious metals such as Au (gold), Cu (copper), Ag (silver), etc.) in the sample, a reasonable peak height threshold is preset. This threshold can be set, for example, to 5%~10% (preferably 8%) of the maximum peak height in the target X-ray spectrum. By traversing all candidate characteristic peak positions, noise spurious peaks with peak heights lower than this threshold are eliminated, and the points with peak heights greater than or equal to the threshold are retained, which are the true characteristic peak positions directly corresponding to the analyte. Therefore, each characteristic peak in sub-step S1031 is a true characteristic peak after removing noise pseudo-peaks.

[0027] After obtaining the positions of the true characteristic peaks, the peak areas and corresponding elements of the true characteristic peaks are determined based on these positions. Each element has a unique characteristic X-ray energy (e.g., the La characteristic peak of Au corresponds to an energy of 9.712 keV, and the Ka characteristic peak of Cu corresponds to an energy of 8.048 keV). Based on this physical characteristic, by calling a pre-stored "element-characteristic energy" database, the energy values ​​corresponding to the selected true characteristic peak positions are matched with the data in the database, thus quickly determining the element type corresponding to each true characteristic peak. Then, a trapezoidal integral algorithm can be used to calculate the peak area of ​​each true characteristic peak. For example, using the intersection of the baselines on both sides of the characteristic peak as the boundary of the integration interval, the signal count rate within the interval is integrated to ensure that the integration result completely covers the signal range of the true characteristic peak, accurately quantifying the total signal of the characteristic peak.

[0028] Sub-step S1032: Calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area.

[0029] Specifically, the area of ​​the continuous background is subtracted from the peak area of ​​each characteristic peak to obtain the net peak area of ​​each characteristic peak. The net peak area of ​​each characteristic peak is used as the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum.

[0030] The peak area of ​​the true characteristic peak in the target X-ray spectrum includes continuous background interference signals, which are typically formed by non-characteristic signals such as X-ray scattering and detector background noise. To ensure the peak area more accurately reflects the actual fluorescence signal intensity of the element, this interference needs to be subtracted. For example, multiple characteristic points can be selected in the baseline-stable regions on both sides of each true characteristic peak. A background fitting curve can be constructed using a linear fitting algorithm, and the area of ​​this curve within the integral interval of the corresponding characteristic peak can be calculated; this is the continuous background area. Subtracting the continuous background area from the total peak area of ​​the true characteristic peaks yields the net peak area, which is the measured characteristic peak intensity of the corresponding element. This value is a quantification of the true fluorescence signal strength of the element.

[0031] Sub-step S1033: Calculate the initial percentage content of each element based on the measured characteristic peak intensity of each element.

[0032] Specifically, through the formula Calculate elements The initial percentage content, of which Represents element The initial percentage content, Represents element The actual characteristic peak intensity, This represents the sum of the measured characteristic peak intensities of all elements, where n is the number of elements.

[0033] Sub-step S1034: Generate the initial simulated spectrum of the sample to be tested based on the initial percentage content of each element.

[0034] Specifically, the initial percentage content of each element is used as the parameter input, and the original theoretical characteristic peak intensity of each element is calculated using the basic parameter method (FP model). The FP model is based on the physical principles of X-ray fluorescence generation (photoelectric effect, fluorescence emission, Compton scattering, etc.). By quantitatively calculating the interaction process between X-rays and each element in the sample, it obtains the theoretical signal intensity of each element's characteristic peak, i.e., the "original theoretical characteristic peak intensity." This intensity only reflects the correlation between element content, experimental parameters, and inherent physical properties, without considering the influence of the actual sample structure on X-ray propagation; it belongs to the "theoretical value under ideal conditions."

[0035] Subsequently, the original theoretical characteristic peak intensities of each element were corrected based on the pre-defined sample structure model. This pre-defined sample structure model includes two types: a coating-substrate composite structure and a homogeneous alloy structure. The coating-substrate composite structure is adapted to the structural assumptions of gold-plated samples, with a pre-defined coating thickness range of 0.1–10 μm; the homogeneous alloy structure is adapted to the structural assumptions of karat gold samples, with a pre-defined assumption of uniform mixing of elements without interlayer differences. These two models provide dual benchmarks for subsequent "structural reverse verification," ensuring that the initial simulated spectra cover the structural characteristics of both samples to be identified.

[0036] Furthermore, based on the selected structural model, simulating the actual propagation process of X-rays within the sample can correct intensity deviations caused by self-absorption effects. If a coating-substrate structure is assumed, X-rays penetrating the surface Au coating will be absorbed by the Au element itself, leading to attenuation of the characteristic peak intensity of the substrate element. In this case, the absorption coefficient is calculated based on the preset coating thickness to weaken the original theoretical characteristic peak intensity of Au and correct the original theoretical characteristic peak intensity of the substrate element (such as Cu and Ag). If a homogeneous alloy structure is assumed, the mutual absorption between different elements (such as Au's absorption of Cu's characteristic X-rays) is calculated to balance and correct the original theoretical characteristic peak intensity of each element. In addition, intensity deviations caused by scattering effects can also be corrected. For example, simulating Compton scattering and Rayleigh scattering of X-rays at structural interfaces (coating-substrate interfaces) or between alloy particles can correct the characteristic peak baseline shift and intensity loss caused by scattering. Intensity deviations caused by fluorescence enhancement effects can also be corrected. For example, simulating the process of a characteristic X-ray of a certain element exciting other elements to produce additional fluorescence (such as Au's La peak exciting Cu to produce fluorescence) can superimpose and correct the original theoretical characteristic peak intensity of the enhanced element.

[0037] After correcting the original theoretical characteristic peak intensities of each element, spectral lines are synthesized based on the corrected original theoretical characteristic peak intensities of all elements to obtain the initial simulated spectrum that conforms to the preset sample structure corresponding to the sample structure model. Specifically, the corrected original theoretical characteristic peak intensities of all elements are summarized, and spectral lines are synthesized according to the inherent energy / wavelength distribution of each element's characteristic peak. That is, with X-ray energy as the horizontal axis and theoretical characteristic peak intensities as the vertical axis, the corrected original theoretical characteristic peak intensities of each element are mapped to their inherent energy positions and superimposed to form complete spectral lines, ultimately obtaining the initial simulated spectrum that conforms to the preset sample structure corresponding to the sample structure model.

[0038] Step S104: Correct the initial simulated spectrum through a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition.

[0039] Specifically, step S104 includes the following sub-steps: Step a: Initialize iteration parameters—use the initial simulated spectrum as the current simulated spectrum for the first iteration, and use the initial percentage content of each element as the original percentage content for the first iteration. ; Step b: Obtain the elements in the current simulated spectrum Theoretical characteristic peak intensity The theoretical characteristic peak intensity is obtained in a similar way to the measured characteristic peak intensity. That is, the peak position of each characteristic peak in the current simulated spectrum is obtained, and then the peak area and the corresponding element are determined according to the peak position of these characteristic peaks. Then, the theoretical characteristic peak intensity of the corresponding element in the current simulated spectrum is calculated according to the peak area, which can be further calculated as the net peak area of ​​each characteristic peak.

[0040] Step c: Calculate the elements Theoretical characteristic peak intensity and elements in the target X-ray spectrum Actual characteristic peak intensity Deviation: ; Step d: According to the formula Update elements Original percentage content The updated percentage content is obtained. , where k is the iteration coefficient; Step e: Based on element Updated percentage content Regenerate a new current simulation spectrum; Step f: Determine the elements in the new current simulated spectrum If the intensity deviation between the current simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition, and if not, the new current simulated spectrum is used as the current simulated spectrum for the next iteration, and the element is... Updated percentage content As the original percentage content for the next iteration Return to step b and repeat; if satisfied, terminate the iteration and determine the new current simulated spectrum as the target simulated spectrum.

[0041] Among them, determining each element in the new current simulated spectrum Whether the intensity deviation of the corresponding element in the target X-ray spectrum meets the preset convergence condition, specifically, determining whether the intensity deviation of each element in the new current simulated spectrum meets the preset convergence condition. Theoretical characteristic peak intensity Corresponding elements in the target X-ray spectrum Actual characteristic peak intensity deviation If the absolute values ​​of all values ​​are less than a threshold, such as 5% or other values, then the preset convergence condition is met, and the iteration is terminated. If not, the iteration continues.

[0042] Step S105: Determine whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum.

[0043] Specifically, if the sample to be tested meets the following conditions one and two, the sample is determined to be a gold-plated sample; otherwise, the sample is determined to be a karat gold sample: Condition 1: The percentage content of Au in the sample after the last iteration is less than 99%. Gold-plated samples have a composite structure of "plating layer-substrate," with Au only present in the surface plating layer and the bottom layer being a non-gold substrate; therefore, their overall Au content must be less than 99%. In contrast, karat gold samples are homogeneous alloys, and their Au content can fluctuate between 37% and 99% (e.g., the Au content of 99K gold is close to 99%). Therefore, samples with an Au content ≥ 99% can be directly excluded as gold-plated samples.

[0044] Condition 2: The intensity ratio L1 of the La characteristic peak to the Lb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L2 of the La characteristic peak to the Lb characteristic peak of Au in the target simulated spectrum satisfy L1 / L2>1.1; or, the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the target simulated spectrum satisfy L3 / L4<0.8.

[0045] Because the "coating-substrate" structure of the gold-plated sample causes abnormal X-ray self-absorption effect, its characteristic peak intensity ratio will deviate from the theoretical ratio of homogeneous alloy (K gold). Therefore, if condition one is met, the sample can be determined to be a gold-plated sample as long as one of the conditions in condition two is met.

[0046] Specifically, when the percentage content of Au in the sample after the last iteration is ≥99%, the sample is directly identified as a karat gold sample regardless of whether the characteristic peak intensity ratio (L1 / L2 or L3 / L4) meets condition two. In addition, when the percentage content of Au after the last iteration is less than 99%, and L1 / L2≤1.1 and L3 / L4≥0.8, the sample is identified as a karat gold sample.

[0047] Therefore, this invention optimizes the matching degree between simulated and measured spectra through iterative optimization until the two reach the optimal fitting state. Based on the optimal matching result, the actual structural characteristics of the sample (such as coating-substrate composite structure or homogeneous alloy structure) can be accurately analyzed, thereby realizing the accurate distinction between gold-plated and K-gold samples and reducing the misjudgment rate in scenarios such as thick coating misjudgment and confusion of similar components.

[0048] participate Figure 3 The present invention also provides a system for identifying gold-plated and karat gold samples, which is used to implement the method for identifying gold-plated and karat gold samples described in the above embodiments. The identification system includes an acquisition module 301, a processing module 302, a generation module 303, a correction module 304, and a judgment module 305.

[0049] The acquisition module 301 is used to acquire the energy spectrum of the sample to be tested and obtain the original X-ray spectrum of the sample; the processing module 302 is used to smooth the original X-ray spectrum to obtain the target X-ray spectrum of the sample; the generation module 303 is used to generate the initial simulated spectrum of the sample to be tested based on the target X-ray spectrum; the correction module 304 is used to correct the initial simulated spectrum through a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the corrected target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition; and the judgment module 305 is used to determine whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum.

[0050] The generation module 303 is specifically used to obtain the peak positions of each characteristic peak in the target X-ray spectrum, determine the peak area and corresponding element of each characteristic peak based on the peak position, calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area, calculate the initial percentage content of each element based on the measured characteristic peak intensity of each element, and generate the initial simulated spectrum of the sample to be tested based on the initial percentage content of each element.

[0051] The present invention will now be described in conjunction with experimental data.

[0052] Application Example 1: Testing gold-plated samples in karat gold applications. For example... Figures 4 to 8 As shown in the figure, "actual spectrum" refers to the target X-ray spectrum, and "simulated spectrum" refers to the current simulated spectrum. When starting the iterative loop, as... Figure 4 As shown, iterative matching begins at the 1st second. The diagram illustrates a comparison between the current simulated spectrum and the target X-ray spectrum during the first iteration. At the 3rd second... Figure 5 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several iterations. The diagram shows that the difference between the two has further decreased; at the 10th second... Figure 6 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several iterations, showing that the difference between the two has further decreased; at the 30th second, Figure 7 This is a schematic diagram comparing the current simulated spectrum and the target X-ray spectrum after several rounds of iteration, showing that the matching degree between the two has reached the best.

[0053] At the 31st second, as Figure 8 As shown, the detected Au content is less than 99%. Simultaneously, the intensity ratio L1 of the La characteristic peak to the Lb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L2 of the La characteristic peak to the Lb characteristic peak of Au in the target simulated spectrum satisfy L1 / L2>1.1. Therefore, the current sample is determined to be a gold-plated sample, and the interface displays the warning: "Warning: The surface may be heavily gold-plated." Application Example 2: Testing karat gold samples in karat gold applications. For example... Figure 9 As shown, the detected Au content is <99%, and the intensity ratio L1 of the La characteristic peak and Lb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L2 of the La characteristic peak and Lb characteristic peak of Au in the target simulated spectrum satisfy L1 / L2<1.1. Therefore, the current sample is determined to be a K gold sample, and no prompt is displayed on the interface.

[0054] Application Example 3: Batch Sample Validation. For example... Figure 10 As shown, Figure 10 The test data table is used to verify multiple groups of gold-plated and karat gold samples. Based on the data of Au “content”, “L1 / L2” and “L3 / L4” in the table, and combined with the judgment conditions of condition one and condition two, the accuracy of the judgment results shown in the table is 100%.

[0055] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for identifying gold-plated and karat gold samples, characterized in that, Includes the following steps: Energy dispersive spectroscopy (EDS) is performed on the sample to obtain the original X-ray spectrum of the sample. The original X-ray spectrum is smoothed to obtain the target X-ray spectrum of the sample to be tested; An initial simulated spectrum of the sample to be tested is generated based on the target X-ray spectrum; The initial simulated spectrum is corrected by a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition. Based on the target simulated spectrum, the sample to be tested is determined to be a gold-plated sample or a karat gold sample.

2. The identification method according to claim 1, characterized in that, The process of generating the initial simulated spectrum of the sample to be tested based on the target X-ray spectrum includes: Obtain the peak position of each characteristic peak in the target X-ray spectrum, and determine the peak area and corresponding element of each characteristic peak based on the peak position; Calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area; The initial percentage content of each element is calculated based on the measured characteristic peak intensity of each element; The initial simulated spectrum of the sample to be tested is generated based on the initial percentage content of each element.

3. The identification method according to claim 2, characterized in that, The step of calculating the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area includes: The net peak area of ​​each characteristic peak is obtained by subtracting the continuous background area from the peak area of ​​each characteristic peak. The net peak area of ​​each characteristic peak is used as the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum.

4. The identification method according to claim 2, characterized in that, The calculation of the initial percentage content of each element based on the measured characteristic peak intensity of each element includes: Through formula Calculate elements The initial percentage content, of which Represents element The initial percentage content, Represents element The actual characteristic peak intensity, This represents the sum of the measured characteristic peak intensities of all elements, where n is the number of elements.

5. The identification method according to claim 2, characterized in that, The step of correcting the initial simulated spectrum using a cyclic iterative algorithm until the characteristic peak intensity deviations of each element in the corrected target simulated spectrum and the corresponding elements in the target X-ray spectrum meet a preset convergence condition includes: Step a: Initialize iteration parameters—Use the initial simulated spectrum as the current simulated spectrum for the first iteration, and use the initial percentage content of each element as the original percentage content for the first iteration. ; Step b: Obtain the elements in the current simulated spectrum Theoretical characteristic peak intensity ; Step c: Calculate elements Theoretical characteristic peak intensity and elements in the target X-ray spectrum Actual characteristic peak intensity Deviation: ; Step d: According to the formula Update elements Original percentage content The updated percentage content is obtained. , where k is the iteration coefficient; Step e: Based on element Updated percentage content Regenerate a new current simulation spectrum; Step f: Determine the elements in the new current simulated spectrum If the deviation of the characteristic peak intensity from the corresponding element in the target X-ray spectrum meets a preset convergence condition, and if not, the new current simulated spectrum is used as the current simulated spectrum for the next iteration, and the element... Updated percentage content As the original percentage content for the next iteration Return to step b and repeat; if satisfied, terminate the iteration and determine the new current simulated spectrum as the target simulated spectrum.

6. The identification method according to claim 5, characterized in that, The step of determining whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum includes: The sample to be tested is determined to be a gold-plated sample if it meets both of the following conditions one and two; otherwise, it is determined to be a karat gold sample: Condition 1: The percentage content of Au element in the sample to be tested after the last iteration is less than 99%; Condition 2: The intensity ratio L1 of the La characteristic peak to the Lb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L2 of the La characteristic peak to the Lb characteristic peak of Au in the target simulated spectrum satisfy L1 / L2>1.1; or, the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the original X-ray spectrum and the intensity ratio L3 of the Ka characteristic peak to the Kb characteristic peak of Au in the target simulated spectrum satisfy L3 / L4<0.

8.

7. The identification method according to claim 2, characterized in that, The process of generating the initial simulated spectrum of the sample based on the initial percentage content of each element includes: Using the initial percentage content of each element as a parameter input, the original theoretical characteristic peak intensity of each element is calculated using the basic parameter method model; The original theoretical characteristic peak intensities of each element are corrected based on the pre-set sample structure model; Based on the original theoretical characteristic peak intensities after correction of all elements, spectral lines are synthesized to obtain the initial simulated spectrum that conforms to the preset sample structure corresponding to the sample structure model.

8. The identification method according to claim 2, characterized in that, The step of obtaining the peak positions of each characteristic peak in the target X-ray spectrum and determining the peak area and corresponding element of each characteristic peak based on the peak positions includes: The peak positions of candidate characteristic peaks in the X-ray spectrum of the target are obtained using the second derivative method; From the candidate feature peaks, feature peaks with peak heights greater than or equal to a preset peak height threshold are selected to obtain the true feature peaks; The peak area and corresponding element of each true characteristic peak are determined based on the peak position of the true characteristic peak.

9. A system for identifying gold-plated and karat gold samples, characterized in that, include: The acquisition module is used to acquire the energy spectrum of the sample to be tested and obtain the original X-ray spectrum of the sample. The processing module is used to smooth the original X-ray spectrum to obtain the target X-ray spectrum of the sample to be tested; The generation module is used to generate an initial simulated spectrum of the sample to be tested based on the target X-ray spectrum; The correction module is used to correct the initial simulated spectrum through a cyclic iterative algorithm until the characteristic peak intensity deviation between each element in the target simulated spectrum and the corresponding element in the target X-ray spectrum meets the preset convergence condition. The judgment module is used to determine whether the sample to be tested is a gold-plated sample or a karat gold sample based on the target simulated spectrum.

10. The identification system according to claim 9, characterized in that, The generation module is specifically used for: Obtain the peak position of each characteristic peak in the target X-ray spectrum, and determine the peak area and corresponding element of each characteristic peak based on the peak position; Calculate the measured characteristic peak intensity of the corresponding element in the target X-ray spectrum based on the peak area; The initial percentage content of each element is calculated based on the measured characteristic peak intensity of each element; The initial simulated spectrum of the sample to be tested is generated based on the initial percentage content of each element.

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